| Mean-Field Controls with Q-learning for Cooperative MARL: Convergence and Complexity Analysis H Gu, X Guo, X Wei, R Xu arXiv preprint arXiv:2002.04131, 2020 | 57* | 2020 |
| Dynamic Programming Principles for Mean-Field Controls with Learning H Gu, X Guo, X Wei, R Xu arXiv preprint arXiv:1911.07314, 2019 | 36* | 2019 |
| Mean-field multiagent reinforcement learning: A decentralized network approach H Gu, X Guo, X Wei, R Xu Mathematics of Operations Research, 2024 | 32 | 2024 |
| Analysis on hybrid fractals PA Ruiz, Y Chen, H Gu, RS Strichartz, Z Zhou arXiv preprint arXiv:1804.05434, 2018 | 9 | 2018 |
| Error estimates for a POD method for solving viscous G-equations in incompressible cellular flows H Gu, J Xin, Z Zhang arXiv preprint arXiv:1812.09853, 2018 | 7 | 2018 |
| BoFL: bayesian optimized local training pace control for energy efficient federated learning H Guo, H Gu, Z Yang, X Wang, EK Lee, N Chandramoorthy, T Eilam, ... Proceedings of the 23rd ACM/IFIP International Middleware Conference, 188-201, 2022 | 3 | 2022 |
| Feasibility and transferability of transfer learning: A mathematical framework H Cao, H Gu, X Guo, M Rosenbaum arXiv preprint arXiv:2301.11542, 2023 | 1 | 2023 |
| An SDE Framework for Adversarial Training, with Convergence and Robustness Analysis H Gu, X Guo ArXiv abs/2105.08037, 2021 | 1 | 2021 |
Xin GuoUC Berkeley, Cornell Univeristy, IBMVerified email at berkeley.edu
